Community Discussions

Hi,I have a view called "Entity" in an existing model with mandatory properties "name", "description" and "isVirtual".Now, I have a new version of "Entity" in which I have decided to implement CogniteDescribable from CDM for name and description, where these fields are not mandatory.When I try to ingest data into the new version of this view, it gives me a non-writable error since the mandatory properties that I had created for the older version is not getting populated.Is there any way to overcome this?Can I map the mandatory container to the container used in CogniteDescribable, so that when I ingest data in the new version, it automatically ingests the mandatory container as well?If yes, can you please share a YAML example of the same to be deployed through toolkit?Please note that both the mandatory and non-mandatory containers have the same name "name".

I am starting the Cognite Data Engineer Learning Path. How to get the access to Cognite Data Fusion platform to practice the learning.

Hello experts,We want to achieve the following workflow:Once a new instance is created/added in our datamodel container Another workflow must be triggered immediately We do not want to create a scheduled based polling to invoke our workflow since our workflow is time sensitive and high importanceCould you please let us know if CDF supports this functionality? Or suggest a way to achieve it.I have explored the CDF in my limited knowledge, I found that subscription is available on Data Model, but it is not enabled in our environment.Could you please help me in this.Thanks,Pranjul Singh  ​​​​​​​    

Reporting as requested. The system seems very unresponsive SQL Transformations internal error. Please report this error to Cognite. Query job ID: a3b2004a-0b5f-4e43-82bd-c396c3bf1a7d | code: 400 | X-Request-ID: 2dd10804-d4c6-9cce-b35c-a1b8af8574c1

When retrieving time-series data registered in CDF using the SDK, I use the following code.client.time_series.search(name="some name")In this case, if I want to take 100 time series, I would need to run the above code 100 times, but is there any SDK that allows me to retrieve this in a list format or something similar?

I'm using python sdk and wanted to query instances based on a condition using “data_modeling.instances.query” method. i have a view “TimeseriesProperty” and it has a direct relation/reference to "TimeseriesPropertyType" view. Is it possible to have a distinct filter on the result, because multiple “TimeseriesProperty” instances can have the same "TimeseriesPropertyType"  instances , we don't want duplicated "TimeseriesPropertyType"  instances coming in response for below query: view_id= ViewId(space="slb-pdm-dm-governed", external_id="TimeseriesProperty",version="2_0")v_id_2_PROP = ViewId(space="slb-pdm-dm-governed", external_id="TimeseriesPropertyType",version="2_0")query= Query( with_= { "TimeseriesProperty":NodeResultSetExpression( limit=10, filter= HasData(views=[view_id])), "TimeseriesP

Hi, As mentioned below, which group to sign up for early adopters of DirectQuery in Power BI? https://docs.cognite.com/cdf/dashboards/guides/powerbi/dq_whyI can’t find relevant group from what I see from here https://hub.cognite.com/groupsAny tips ? :)Thanks, 

We have customers using InfluxDB as a local on-prem storage mechanism. What’s the best extractor to use to push this data to CDF? I’ve heard OPC-UA is the way to do it, but what I find online are ways to store OPC-UA data into Influx, but not ways to get InfluxDB data into a OPC-UA server so I could use the OPC-UA extractor to get it into CDF.

Our team is handling 3D models in various file formats and applying colors to different models before importing them into CDF. Additionally, we are applying textures to models using Navisworks Simulate and exporting them in .nwd or .fbx formats. All related files are zipped before uploading them in CDF.According to the Cognite 3D documentation, this should be possible. However, when we import the models, the colors do not appear as expected. Could you provide guidance on the correct procedure to ensure that colors and textures are retained? Is there a specific workflow or setting we should follow?

Use CaseI am building a dashboard in Power BI that will visualize Events from CDF (about one million events per year). So to make the solution scale I want to use incremental refresh of the semantic model so I only refresh the model with the newest Events since the last refresh.I have followed your tutorial on Incremental refresh (which seems copy/paste of Microsoft’s tutorial), but I still have questions:What happens if the StartTime attribute of an Event is a date/time/zone when loaded into the model? The attribute needs to be a date/time type, which means I need to convert the type first. How will the incremental refresh work if the model needs to load the data in order to convert the type, and then apply the RangeStart/RangeEnd filters? Can I use Incremental refersh with the new REST API Connector? When I load events with the new connector I get the start times as number of milliseconds since epoch. So the type conversion from above al

I have a data model and would like to retrieve or list nodes from a specific view. Specifically, I want to list nodes that have been created or updated, for instance in the last 30 days,  using Pygen.I understand that Pygen provides filtering capabilities to filter based on view properties or columns. However, I don't see a way to filter by the updated date, which is a column automatically created under the data_record column when inserting new nodes with Pygen. It seems Pygen doesn’t expose this field as a filter parameter.Is there a way to apply a filter on data_record.updated_date using Pygen?

The new CDF Power BI REST connector has been certified by Microsoft and is now included in the latest Power BI desktop version and deployed in the Power BI online service.What's new with the Power BI REST connector:Flexible authentication: Connect Power BI with any IdP supported by CDF (the legacy OData connector only worked with Azure Entra ID) Broader data access: Fetch data from OData services (just like the legacy connector) Access data from Data Models using GraphQL Connect to any GA CDF API endpoint Significant performance boost: Up to 10x faster when using regular REST endpoints compared to fetching the same data via ODataThe connector is currently in Beta, and we're eager to hear customer feedback before promoting it to GA. The documentation for the new connector is available 

Hi Just wondering if CDF extractors/connectors has a support to fetch DFOS data, say for example to measure temperature along the line. Access may perhaps be through the third party SDK or a native connector. Also interesting would be how such high frequency data can be modelled in CDF core and solution models correctly. Any pointers would be of great help!  RegardsAlex 

Hi team, I want to import some functions from util folder which is same directory of the folder in which handler.py. As files in util folder is being used by other cognite functions too, I can’t keep the files of util folder in function_folder but at the time of importing functions from files of util folder and after deploying cognite function it gives import error as  so basically structure is Repofunction_folder- file1 and handler.pyutil_folder - file2 and file 3 And I want to use methods from file 2 into handler.py and I have added __init__.py in util folder 2025-04-04T12:17+05:30 : Traceback (most recent call last): 2025-04-04T12:17+05:30 : File "/home/site/wwwroot/function/_cognite_function_entry_point.py", line 297, in import_user_module 2025-04-04T12:17+05:30 : handler = importlib.import_module(handler_module_path) 2025-04-04T12:17+05:30 : File "/usr/local/lib/python3.9/importlib/__init__.py", line 127, in import_module 2025-0

Hello As our industrial data evolves; we're facing challenges with schema versioning specifically when modifying / extending the properties of existing asset or time series types in Cognite Data Fusion (CDF).  🙂For instance; adding new fields or changing data types (e.g., integer to float) in metadata often breaks downstream pipelines or applications that expect the original structure. CDF doesn’t enforce a strict schema, but how do others handle backward compatibility in real-world use?😐We’ve experimented with versioned types and custom labels to signal changes, but this quickly becomes hard to manage at scale. Some of our consumers rely on fixed field names, and introducing Salesforce Developer Course breaking changes results in unexpected behaviors in the SDKs or fusion apps.😐Is there a recommended practice for managing

Hello, As per the docuementaiton Pygen exposes a `graphql_query` method. However, I’m not able to find it. Could you please help? version used:  cognite-pygen==1.2.1Thanks

Hello, While testing data gouvernance feature per space in the data model service, we noticed that it does work on the instance level but not on the data models level. Here are the tests conducted: Test 1:We tested giving access to users to only instances that are in a specific space but applying the following ACL :  - dataModelInstancesAcl: actions: - READ scope: spaceIdScope: { spaceIds: ['test'] }When requesting the data model, only instances in the test space are returned. ACL works on instance level. Perfect!Test 2: When applying a similar ACL on the data model level :  - dataModelsAcl: actions: - READ scope: spaceIdScope: { spaceIds: ['not_that_important_data_models'] }In this case, we notice that we get revoked access to all data models, even data model in not_tha

Hi,I would like to check whether there is any CDF Admin UI or available APIs that provide the telemetry and usage-related insights such:​​​​​ User activity logs such logins, user actions, dataset access, frequency of use API usage metering such calls made by service accounts or integrations, volume over time Application usage tracking such as which integrations/apps are active, which endpoints are being used and etc. Quota and resource usage tracking, like number of API calls, storage/compute loads. Are there any CDF admin dashboards, telemetry APIs, or audit logs available for this purpose?Please advise.  Thanks

Hi!Is there a way to enable cascading deletes for instances for both direct relations and edges? Edit: I posted in the wrong group, but i don’t think i can delete. 

In Open Industrial Data (OID), we have moved away from API keys. Open Industrial Data currently supports Open ID connect. You can check out more on how to configure OpenID Connect on Open Industrial Data.If you are planning to use OID and authenticate using client credentials flow, you will need a client secret from the app registration on the Azure Active Directory. Go to Open Industrial Data and you will observe there is a widget for generating a new client secret IDIn the drop down, you can select two options:Other: Use this if you are using Postman or Pyth

I would like to know what to fill in BI to be able to connect on CDF. I tried to use  that how on the course, but gives a error to add the organization name. publicdata?tenantID=48d5043c-cf70-4c49-881c-c638f5796997

 Hello, I’m having this error while using CDF latest Spark datasource. I was only able to make it work using 2.1.10 version (com.cognite.spark.datasource:cdf-spark-datasource_2.12:2.1.10).  Could you please take a look?  Thank you ! 

Hello, We are using cdf toolkit to deploy our container, views and data models.We recently added many new views, these views are dependent. i.e: they reference each other in the properties through a source block or via implements block. Here an examples of these view dependencies:- externalId: View1 implements: [] name: View1 properties: test: container: externalId: Container1 space: some_space type: container containerPropertyIdentifier: Test name: test source: externalId: View2 space: some_space type: view version: v1 space: some_space version: v1- externalId: View2 implements: [] name: View2 properties: wow: container: externalId: Container2 space: some_space type: container

In Cognite Academy Fundamentals : Working With CDF: Contextualize, I have followed all of the instructions several times for Entity Matching and, in all instances, get “No matches found”, so there is nothing to confirm or write to CDF.  What am I missing here?

Using PBI Desktop and Cognites Rest API Connector betaWhen configuring the GraphQL parameters of Space, Datamodel, version and queryThere is a problem when pasting a query that was copied from the Query Explorer or even notepad into the query input boxIt is truncating the query string at the first carriage return CR and or Line Feed LFIf all CR and LF are removed from the query string, it will paste properly and run properly.